Fr. 100.00

Algorithmic Information Dynamics - A Computational Approach to Causality With Applications to Living

English · Hardback

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Description

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Aimed at graduate students and researchers, this book offers a model-driven approach to the study and manipulation of dynamical systems. Based on an online course hosted by the Complexity Explorer, it uses analytical tools from information theory and complexity science to tackle key challenges in network and systems biology.

List of contents










Introduction; Part I. Preliminaries: 1. A computational approach to causality; 2. Networks: from structure to dynamics; 3. Information and computability theories; Part II. Theory and Methods: 4. Algorithmic information theory; 5. The coding theorem method (CTM); 6. The block decomposition method (BDM); 7. Graph and tensor complexity; 8. Algorithmic information dynamics (AID); Part III. Applications: 9. From theory to practice; 10. Algorithmic dynamics in artificial environments; 11. Applications to integer and behavioural sequences; 12. Applications to evolutionary biology; Postface; Appendix: Mutual and conditional BDM; Glossary.

About the author

Hector Zenil is a senior researcher at the Alan Turing Institute, British Library, researcher at the Department of Chemical Engineering and Biotechnology, University of Cambridge and the leader of the Algorithmic Dynamics Lab at the Karolinska Institute in Sweden. Previous positions include Computer Science faculty member at the University of Oxford, NASA Payload team member for the Mars Gravity Biosatellite at the Massachusetts Institute of Technology, and researcher at the Evolutionary and Behavioural Theory Lab at the University of Sheffield. He helped develop the factual answering Artificial Intelligence engine behind Siri and Alexa at Wolfram Research. He has published over 120 peer-reviewed papers, edited six books, is Editor of the journal Complex Systems, and the author of Methods and Applications of Algorithmic Complexity (2022).Narsis A. Kiani is a senior researcher at the Department of Oncology-Pathology and Lab leader at the Algorithmic Dynamics Lab, Center for Molecular Medicine, Karolinska Institute in Stockholm, Sweden. She received a BEng in medical engineering and a BSc in pure mathematics (Amirkabir University of Technology (Polytechnic of Tehran), MSc (Kharazmi University), and Ph.D. in applied mathematics (Tehran Science & Research Branch Azad University). She was Vinnova-Marie Curie fellow at Karolinska Institute (2014) and held a postdoctoral position at BioQuant, Heidelberg University. She is the co-editor of Networks of Networks in Biology: Concepts, Tools and Applications (2021).Jesper Tegnér is a Professor of Bioscience and Computer Science at King Abdullah University of Sciences and Technology and Adjunct Chaired Strategic Professor of Computational Medicine at Karolinska Institute. He was awarded a Research Fellowship position from the Alfred P. Sloan Foundation (USA). Dr. Tegnér was recruited to the first Chaired Full Professorship in Computational Biology (Dept. of Physics) in Sweden 4.5 years (February 2002) after completing his Ph.D. Since January 2010 he is a Strategic Professor Computational Medicine at Center for Molecular Medicine, Director for the Unit of Computational Medicine, Dept. of Medicine, Solna Karolinska Institutet and Karolinska University Hospital.

Summary

Aimed at graduate students and researchers, this book offers a model-driven approach to the study and manipulation of dynamical systems. Based on an online course hosted by the Complexity Explorer, it uses analytical tools from information theory and complexity science to tackle key challenges in network and systems biology.

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